Data centric trust evaluation and prediction framework for IOT

© 2017 ITU. Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas

Trust and privacy in distributed work groups

Proceedings of the 2nd International Workshop on Social Computing, Behavioral Modeling and PredictionTrust plays an important role in both group cooperation and economic exchange. As new technologies emerge for communication and exchange, established mechanisms of trust are disrupted or distorted, which can lead to the breakdown of cooperation or to increasing fraud in exchange. This paper examines whether and how personal privacy information about members of distributed work groups influences individuals' cooperation and privacy behavior in the group. Specifically, we examine whether people use others' privacy settings as signals of trustworthiness that affect group cooperation. In addition, we examine how individual privacy preferences relate to trustworthy behavior. Understanding how people interact with others in online settings, in particular when they have limited information, has important implications for geographically distributed groups enabled through new information technologies. In addition, understanding how people might use information gleaned from technology usage, such as personal privacy settings, particularly in the absence of other information, has implications for understanding many potential situations that arise in pervasively networked environments.Preprin

Trust Based Participant Driven Privacy Control in Participatory Sensing

Widespread use of sensors and multisensory personal devices generate a lot of personal information. Sharing this information with others could help in various ways. However, this information may be misused when shared with all. Sharing of information between trusted parties overcomes this problem. This paper describes a model to share information based on interactions and opinions to build trust among peers. It also considers institutional and other controls, which influence the behaviour of the peers. The trust and control build confidence. The computed confidence bespeaks whether to reveal information or not thereby increasing trusted cooperation among peers.Comment: 14 page

Intrusiveness, Trust and Argumentation: Using Automated Negotiation to Inhibit the Transmission of Disruptive Information

The question of how to promote the growth and diffusion of information has been extensively addressed by a wide research community. A common assumption underpinning most studies is that the information to be transmitted is useful and of high quality. In this paper, we endorse a complementary perspective. We investigate how the growth and diffusion of high quality information can be managed and maximized by preventing, dampening and minimizing the diffusion of low quality, unwanted information. To this end, we focus on the conflict between pervasive computing environments and the joint activities undertaken in parallel local social contexts. When technologies for distributed activities (e.g. mobile technology) develop, both artifacts and services that enable people to participate in non-local contexts are likely to intrude on local situations. As a mechanism for minimizing the intrusion of the technology, we develop a computational model of argumentation-based negotiation among autonomous agents. A key component in the model is played by trust: what arguments are used and how they are evaluated depend on how trustworthy the agents judge one another. To gain an insight into the implications of the model, we conduct a number of virtual experiments. Results enable us to explore how intrusiveness is affected by trust, the negotiation network and the agents' abilities of conducting argumentation

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

Understanding collaboration in volunteer computing systems

Volunteer computing is a paradigm in which devices participating in a distributed environment share part of their resources to help others perform their activities. The effectiveness of this computing paradigm depends on the collaboration attitude adopted by the participating devices. Unfortunately for software designers it is not clear how to contribute with local resources to the shared environment without compromising resources that could then be required by the contributors. Therefore, many designers adopt a conservative position when defining the collaboration strategy to be embedded in volunteer computing applications. This position produces an underutilization of the devices’ local resources and reduces the effectiveness of these solutions. This article presents a study that helps designers understand the impact of adopting a particular collaboration attitude to contribute with local resources to the distributed shared environment. The study considers five collaboration strategies, which are analyzed in computing environments with both, abundance and scarcity of resources. The obtained results indicate that collaboration strategies based on effort-based incentives work better than those using contribution-based incentives. These results also show that the use of effort-based incentives does not jeopardize the availability of local resources for the local needs.Peer ReviewedPostprint (published version